视网膜图像中血管的自动检测

A. Elbalaoui, M. Fakir, K. Taifi, A. Merbouha
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引用次数: 33

摘要

视网膜血管的自动检测和血管直径的测量对糖尿病视网膜病变、青光眼、高血压等眼病的诊断和治疗具有重要意义。本文提出了一种检测眼底视网膜图像中血管的新方法。该方法包括三个主要步骤。第一步是对视网膜图像进行预处理,通过评价几种图像增强技术来改善视网膜图像。在第二步中,通常使用血管过滤器来增强血管。最后根据血管性滤波器输出的自适应阈值设计了Hessian多尺度增强滤波器,用于血管检测。在三个公开可用的视网膜图像数据库(DRIVE、STARE和CHASE_DB)上,使用包括准确性、灵敏度和特异性在内的一系列措施,对算法的性能进行了比较和分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Detection of Blood Vessel in Retinal Images
Automatic detection of retinal blood vessels and measurement of vessel diameter are very much important for the diagnosis and the treatment of different ocular diseases including diabetic retinopathy (DR), glaucoma and hypertension. In this paper, we present a novel method to detect blood vessels in the fundus retinal images. The proposed method consists of three main steps. The first step is pre-processing of retinal image to improve the retinal images by evaluation of several image enhancement techniques. In the second step, the vesselness filter is usually used to enhance the blood vessels. Finally Hessian multiscale enhancement filter is designed from the adaptive thresholding of the output of the vesselness filter for vessels detection. The performance of algorithms is compared and analyzed on three publicly available databases (DRIVE, STARE and CHASE_DB) of retinal images using a number of measures, which include accuracy, sensitivity, and specificity.
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